1. Field of the Invention
This patent specification generally relates to grayscale and geometric registration of images such as medical images. More specifically, simultaneous grayscale and geometric registration of two or more images, such as mammograms, for facilitating visual comparison thereof and enhancing the speed and reliability of computer aided diagnosis (CAD) detection of medical abnormalities, are disclosed.
2. Description of Related Art
Systems for computer aided diagnosis (CAD) assist radiologists in the detection and classification of abnormal lesions in medical images. The purpose of such devices, as described in U.S. Pat. No. 5,815,591 entitled “Method and Apparatus for Fast Detection of Spiculated Lesions in Digital Mammograms” and issued on Sep. 29, 1998 to Roehrig, et. al., the entirety of which is hereby incorporated by reference herein, is to direct the attention of a radiologist to suspicious areas of the medical image that may reflect a threatening condition. While not a replacement for the experienced radiologist, CAD systems are designed to increase efficiency and reduce error, as a typical radiologist may be required to examine hundreds of medical images per day, which can lead to the possibility of a missed diagnosis due to human error.
Desired characteristics of a CAD system for analyzing medical images such as mammograms include high speed (requiring less processing time), high sensitivity or precision (the ability to detect more subtle indications of abnormalities), and/or high accuracy (lower false positives, i.e., the number of areas marked “suspicious” by the CAD system which, in reality, are not suspicious or indicative of a possibly cancerous condition and lower false negatives, also called “misses”). It is noted that although “mammogram” is sometimes used in the art to depict a set of four related films or views but sometimes used to depict one such view, for clarity purposes, the term “mammogram” shall correspond to one of the related films or views taken during the mammography process.
Most commercial CAD systems today generally usually treat each digital medical image separately. In these CAD systems, the plurality of digital or digitized medical images are processed separately by the CAD system for detecting suspicious lesions. However, in radiology practice it is often useful to compare similar medical image views taken at different times and temporal comparisons may form an important part of the diagnostic procedure. Temporal comparisons can be made to detect interval changes indicating lesion growth, to monitor progression of a disease, and/or to estimate the effect of treatment.
One area where temporal comparison of medical images plays a major role is breast cancer screening using mammography. For example, if a breast develops a potentially suspicious lesion over a period of time as reflected by periodic mammograms of that breast, such as every twelve months, the likelihood increases that it is a true lesion. Studies have shown that the use of prior mammograms in screening effectively reduces the number of false positive referrals. See for example, Thurfjell, M. G., Vitak, B., Azavedo E., Svane G., Thurfjell E., “Effect on Sensitivity and Specificity of Mammography Screening With or Without Comparison of Old Mammograms,” ACTA Radiologica, 41(1) (2000) 52-56; and Burnside, E. S., Sickles, E. A., Sohlich R. E., Dee K. E., “Differential Value of Comparison With Previous Examinations in Diagnostic Versus Screening Mammography,” American Journal of Roentgenology, 179(5) (2002) 1173-1177, the entireties of which are incorporated by reference herein. This results from the fact that the use of prior mammograms allows radiologists to distinguish lesions that grow from normal dense structures in the breast that somehow look suspicious. Temporal comparison of mammograms in a CAD system is described in U.S. Pat. No. 6,075,879 to Roehrig et. al, which is incorporated by reference herein.
Breast cancer in women is a serious health problem, the American Cancer Society currently estimating that over 180,000 U.S. women are diagnosed with breast cancer each year. Breast cancer is the second major cause of cancer death among women, the American Cancer Society also estimating that breast cancer causes the death of over 44,000 U.S. women each year. While at present there is no means for preventing breast cancer, early detection of the disease prolongs life expectancy and decreases the likelihood of the need for a total mastectomy.
Currently, mammography using x-rays is the most common method of detecting and analyzing breast lesions. The current trend, however, is toward digital mammography. In the Netherlands, for example, where a nation-wide breast cancer screening program is implemented, about two million women in the 50 to 75 age group are invited once every two years for screening mammography. With an attendance of 80%, about 800,000 women have a screening mammography every year. It is expected that within the next few years all screening units in the country will convert to digital mammography. During a two year transition period, digital mammograms will need to be read in combination with the prior film-screen mammograms. Currently, it is expected that all most recent prior film-screen mammograms will be digitized to allow soft-copy reading.
Sometimes, temporal images are subtracted to enhance areas where differences occur. However, in conventional radiology the review of temporal image pairs may be seriously hampered by differences in acquisition. To some extent, positioning changes can be dealt with by geometric registration algorithms, the development of which received a lot of attention in recent years. See for example, Sallam, M. Y., Bowyer, K. W., “Registration and Difference Analysis of Corresponding Mammogram Images, Medical Image Analysis,” 3(2) (1999) 103-118; and Wirth, M. A., Narhan, J., Gray, D., “Non-Rigid Mammogram Registration Using Mutual Information,” Proc. SPIE Medical Imaging 2002: Image Processing, vol. 4684 (2002) 562-573, the entireties of which are incorporated by reference herein.
The differences in acquisition are generally attributed to changes in exposure and to different screen-film imaging and/or digital imaging systems. These differences may cause subsequent mammograms to appear dramatically different and thus reduce the effectiveness of temporal comparisons. Thus, for example, when visually comparing a current-year mammogram to a prior-year mammogram on a softcopy display, a radiologist can have difficulty detecting subtle anatomical differences between the mammograms, because their different acquisition parameters can make them appear very different in terms of grayscale levels. These differences may not be easily normalized as they may induce nonlinear gray scale changes. Although radiologists may adjust the relative contrast, brightness and/or position of the threshold of the S-curve (the HD-curve, named after Hurter and Driffeld) of one or more images, such a process can be inaccurate, tedious, annoying, and time-consuming and may reduce performance and efficiency and induce human errors. In other words, these acquisition differences cannot be easily or quickly corrected by the radiologists during display. In addition to negatively affecting visual comparison thereof, differences in grayscale settings/parameters between two temporally distinct mammograms of the same breast can be a disadvantage for temporal comparisons thereof in a CAD system, such as that described in U.S. Pat. No. 6,075,879 supra.
Accordingly, it would be desirable to facilitate visual comparison of two or more mammograms of a breast taken at different times and/or under different acquisition conditions. It would be further desirable to provide a computer-aided diagnosis (CAD) system that can effectively use information from multiple digital or digitized medical images, including sets taken at different times and/or under different acquisition parameters, to detect anatomical abnormalities therein. In a mammography setting, the multiple mammograms would be of the same or similar mammogram view of the same patient.